Top 3 Automation Myths

Artificial Intelligence (AI) and robotics are both very popular topics in the media today, which comes as no surprise. Recent developments in AI and robotic technology have encouraged an increase in adoption of automation tools rates across the world. With all this coverage, it’s common to hear myths and hyperbolic statements about how this new technology will impact our lives and careers. So in order to help you keep the facts straight, here are some of the most common automation myths about robotics and AI that we’ve heard recently.

1. Automation Myth: Robots Will Take Our Jobs

This seems to be a recurring headline in the newspapers. The myth is based on some research: for example, Gartner predicts that 1/3 of jobs could be automated by the year 2025. But to jump from “portions of our work could be automated” to “AI will take all of our jobs” is a stretch. A new OECD-commissioned report has provided some much needed context and argues that some studies may have overestimated the risk for automation of jobs because its underlying assumption was “that whole occupations rather than single job-tasks are automated by technology.” Overall, when accounting for the “heterogeneity of workers’ tasks within occupations,” the new study finds that on average, across the 21 OECD countries, only 9% of jobs are automatable. It’s true that repetitive, high volume, data-intensive tasks can be assigned to automation tools, but instead of replacing jobs, this frees up more time to be spent towards more creative tasks, to help clients, or more generally, the company. For example, 30 years ago we worked with telephones and pens and paper, and now for many of us the only thing on our desk is a computer. Remember, people said PCs would take our jobs, but instead they’ve just allowed us to focus our work towards other tasks.

2. Automation Myth: AI is Plug and Play

Many people think that automation software comes preloaded with comprehensive levels of “know-how”. Recently, we talked about the difference between the statistical and deterministic approach to AI. These two different approaches are the ways through which software and machines are programmed with knowledge. While there are many differences, the most notable is in reference to accuracy. With the statistical (machine learning) approach, 100% of all processes are automated but with only 70% accuracy. However, with the deterministic approach, 70% of the process is automated with 100% accuracy. While each approach has its use cases, deterministic is better when being wrong 30% of the time is unacceptable to a business.

3. Automation Myth: Robots Are Autonomous in All Aspects

While robotics have many practical applications to a business, one of the most noted is the ability to work 24/7, day and night. As this can be done without the supervision of employees, automation can increase the amount of tasks completed in a day without the increase in labor costs. However, automation tools can’t function without the guidance of a business user or technician. There needs to be someone to help design, implement, and adjust the technological framework.
Automation can be a very powerful tool when used in the right scenario, but not all business processes can be automated. Take for example Robotic Process Automation (RPA) in the financial services. RPA and other automation tools excel when it comes to repetitive, routine-based tasks, ultimately minimizing regulation and compliance risks. But these systems can’t be considered Business Process Optimization (BPO) or Business Process Management (BMP) systems. There’s only certain parts of the business where automation is an advantage. To learn more about process automation in financial services, please download the eBook “From Henry Ford to High Finance: Why Automation in Finance is Booming”.
While the robotic and AI technology continue to develop, what we can be sure of is that automation will continue to help expand capacity and allow business users to focus more on what’s important to the business. But we need to learn to sort the automation myths from the automation facts and look at the overall progress of these tools in terms of how they can help us to do our job better because after all they are tools not competitors. As Present John F. Kennedy said back in 1962, “If men have the talent to invent new machines that put men out of work, they have the talent to put those men back to work”.

Arden Manning

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